More powerful multiple testing under dependence via randomization

Z Xu, A Ramdas - arXiv preprint arXiv:2305.11126, 2023 - arxiv.org
We show that two procedures for false discovery rate (FDR) control--the Benjamini-Yekutieli
procedure for dependent p-values, and the e-Benjamini-Hochberg procedure for dependent …

Online closed testing with e-values

L Fischer, A Ramdas - arXiv preprint arXiv:2407.15733, 2024 - arxiv.org
In contemporary research, data scientists often test an infinite sequence of hypotheses $
H_1, H_2,\ldots $ one by one, and are required to make real-time decisions without knowing …

Boosting e-BH via conditional calibration

J Lee, Z Ren - arXiv preprint arXiv:2404.17562, 2024 - arxiv.org
The e-BH procedure is an e-value-based multiple testing procedure that provably controls
the false discovery rate (FDR) under any dependence structure between the e-values …

An online generalization of the e-BH procedure

L Fischer, A Ramdas - arXiv preprint arXiv:2407.20683, 2024 - arxiv.org
In online multiple testing the hypotheses arrive one-by-one over time and at each time it
must be decided on the current hypothesis solely based on the data and hypotheses …